Abstract

AbstractMultiplicity considerations play an important role in clinical trials with multiple treatment comparisons or endpoints. This article provides a high‐level review of key concepts in multiple testing, including control of false‐positive outcomes and popular multiplicity adjustments. The article also introduces and compares important statistical principles (union‐intersection, closed testing and partitioning principles) which provide a foundation for widely used multiple tests. The statistical methods described in this article are illustrated using examples from clinical trials.

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